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---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-finetuned-panx-all
results: []
language:
- en
- de
- it
- fr
metrics:
- f1
library_name: transformers
---
# xlm-roberta-base-finetuned-panx-all
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the XTREME PANX dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1758
- F1 Score: 0.8558
## Model description
This model is a fine-tuned version of xlm-roberta-base on a concatenated dataset combining multiple languages, specifically German (de) and French (fr). The model has been trained for token classification tasks and achieves competitive F1-scores across various languages.
## Intended uses
Named Entity Recognition (NER) tasks across multiple languages.
Token classification tasks that benefit from multilingual training data.
## Limitations
Performance may vary on languages not seen during training.
The model is fine-tuned on specific datasets and may require further fine-tuning or adjustments for other tasks or domains.
## Training and evaluation data
The model was fine-tuned on a combination of German and French datasets, with the training data shuffled and concatenated to form a multilingual corpus. Additionally, the model was evaluated on multiple languages, showing robust performance across different linguistic datasets.
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.299 | 1.0 | 835 | 0.2074 | 0.8078 |
| 0.1587 | 2.0 | 1670 | 0.1705 | 0.8461 |
| 0.1012 | 3.0 | 2505 | 0.1758 | 0.8558 |
### Evaluation results
The model was evaluated on multiple languages, achieving the following F1-scores:
| Evaluated on | de | fr | it | en |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| Fine-tune on | | | | |
| de |0.8658 | 0.7021 | 0.6877 | 0.5830 |
| each |0.8658 | 0.8411 | 0.8180 | 0.6870 |
| all |0.8685 | 0.8654 | 0.8669 | 0.7678 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |